Abstract: Actor–Agent Communities (or AACs) are a particular type of Complex System that involve the collaboration of multiple human and artificial agents for the realization of a common mission. The definition and development of such communities give rise to a number of research challenges which are addressed in the DECIS Lab, a partnership among academia, the research community and industry.
Abstract: We describe several principles for designing Actor-Agent Communities (AAC) as collectives of autonomous problem solving entities (software agents and human experts) that self-organize and collaborate at solving complex problems. One of the main distinctive aspects of the AAC is their ability to integrate in a meaningful way the expertise and reasoning of humans with different information processing algorithms performed by software agents, without requiring a unique and complete description of the problem and solution spaces.
Abstract: This research report discusses human group characteristics as a stepping stone to study human-agent team characteristics and dynamics. A human-agent team, or so called actor-agent team (AAT) is a group of humans and agents who interact in a coherent and coordinated way towards a common goal. The concept of AATs relates to actor-agent communities (AACs), as AACs are groups of humans and artificial systems (socio-technical information systems) that intimately work together to achieve a common goal (i.e. solve a problem) (Iacob et al., 2009).
AATs are envisioned to increase human performance in (among others) safety and security domains, emergency management, and traffic control. However, the concept of AATs brings many challenges. Besides the realisation of agents as teammembers, and the realisation of real-world AATs, the interaction between agents and humans is a challenge. If agents are to become (task performing) group members, team membership requires much from agents regarding human-agent interaction. How should agents be designed to become teammembers in an AAT? How can humans best interact with agents? When do trust an agent, or rely on it?
This document discusses human group characteristics to draw implications for AAT dynamics. This document is a follow-up of Gouman et al. (2008) in which stages of team development, group membership and cohesion, subgroups, norms, roles, status, and leadership were discussed. The current report first addresses communication and decision making, after which team performance and implications for AATs are discussed.
Abstract: The main goal of this thesis is to provide a first overview of the current architectures the most able to design a cognitive agent. The notion of cognitive agent is in line with the Actor-Agent Community (AAC) project of D-CIS Lab (second part of this thesis). This project aims to design a prototype of an artificial system with cognitive capabilities (the cognitive agent) capable to interact with humans within a team (the Actor-Agent Community).